Toward understanding the emergence of life: A dual function of the system of nucleotides in the metabolically closed autopoietic organization
Bibliographic record
Abstract
General structure of metabolism includes the reproduction of catalysts that govern metabolism. In this structure, the system becomes autopoietic in the sense of Maturana and Varela, and it is closed to efficient causation as defined by Robert Rosen. The autopoietic maintenance and operation of the catalysts takes place via the set of free nucleotides while the synthesis of catalysts occurs via the information encoded by the set of nucleotides arranged in polymers of RNA and DNA. Both energy charge and genetic information use the components of the same pool of nucleoside triphosphates, which is equilibrated by thermodynamic buffering enzymes such as nucleoside diphosphate kinase and adenylate kinase. This occurs in a way that the system becomes internally stable and metabolically closed, which initially could be realized at the level of ribozymes catalyzing basic metabolic reactions as well as own reproduction. The function of ATP, GTP, UTP, and CTP is dual, as these species participate both in the general metabolism as free nucleotides and in the transfer of genetic information via covalent polymerization to nucleic acids. The changes in their pools directly impact both bioenergetic pathways and nucleic acid turnover. Here we outline the concept of metabolic closure of biosystems grounded in the dual function of nucleotide coenzymes that serve both as energetic and informational molecules and through this duality generate the autopoietic performance and the ability for codepoietic evolutionary transformations of living systems starting from the emergence of prebiotic systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.017 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".